Zobrazeno 1 - 10
of 7 074
pro vyhledávání: '"A Ascoli"'
Geometric trees are characterized by their tree-structured layout and spatially constrained nodes and edges, which significantly impacts their topological attributes. This inherent hierarchical structure plays a crucial role in domains such as neuron
Externí odkaz:
http://arxiv.org/abs/2408.08799
Autor:
Singh, Chandan, Ntinas, Vasileios, Prousalis, Dimitrios, Wang, Yongmin, Demirkol, Ahmet Samil, Messaris, Ioannis, Rana, Vikas, Menzel, Stephan, Ascoli, Alon, Tetzlaff, Ronald
This paper introduces an innovative graphical analysis tool for investigating the dynamics of Memristor Cellular Nonlinear Networks (M-CNNs) featuring 2nd-order processing elements, known as M-CNN cells. In the era of specialized hardware catering to
Externí odkaz:
http://arxiv.org/abs/2408.03260
ESM+: Modern Insights into Perspective on Text-to-SQL Evaluation in the Age of Large Language Models
The task of Text-to-SQL enables anyone to retrieve information from SQL databases using natural language. Despite several challenges, recent models have made remarkable advancements in this task using large language models (LLMs). Interestingly, we f
Externí odkaz:
http://arxiv.org/abs/2407.07313
Spiking neural networks drawing inspiration from biological constraints of the brain promise an energy-efficient paradigm for artificial intelligence. However, challenges exist in identifying guiding principles to train these networks in a robust fas
Externí odkaz:
http://arxiv.org/abs/2404.15627
Autor:
Wheeler, Diek W., Ascoli, Giorgio A.
Many fields, such as neuroscience, are experiencing the vast proliferation of cellular data, underscoring the need for organizing and interpreting large datasets. A popular approach partitions data into manageable subsets via hierarchical clustering,
Externí odkaz:
http://arxiv.org/abs/2403.03318
Autor:
Messaris, Ioannis, Ascoli, Alon, Demirkol, Ahmet S., Ntinas, Vasileios, Prousalis, Dimitrios, Tetzlaff, Ronald
In this theoretical study, we focus on the high-frequency response of the electrothermal NbO2-Mott threshold switch, a real-world electronic device, which has been proved to be relevant in several applications and is classified as a volatile memristo
Externí odkaz:
http://arxiv.org/abs/2401.10924
We introduce ODEFormer, the first transformer able to infer multidimensional ordinary differential equation (ODE) systems in symbolic form from the observation of a single solution trajectory. We perform extensive evaluations on two datasets: (i) the
Externí odkaz:
http://arxiv.org/abs/2310.05573
In this work, we introduce Boolformer, the first Transformer architecture trained to perform end-to-end symbolic regression of Boolean functions. First, we show that it can predict compact formulas for complex functions which were not seen during tra
Externí odkaz:
http://arxiv.org/abs/2309.12207
Autor:
Ascoli, Ruben, Betti, Livia, Cheigh, Justin, Iosevich, Alex, Jeong, Ryan, Liu, Xuyan, McDonald, Brian, Milgrim, Wyatt, Miller, Steven J., Acosta, Francisco Romero, Iannuzzelli, Santiago Velazquez
Let $\mathbb{F}_q^d$ be the $d$-dimensional vector space over the finite field with $q$ elements. For a subset $E\subseteq \mathbb{F}_q^d$ and a fixed nonzero $t\in \mathbb{F}_q$, let $\mathcal{H}_t(E)=\{h_y: y\in E\}$, where $h_y$ is the indicator f
Externí odkaz:
http://arxiv.org/abs/2307.10425
Autor:
Jelassi, Samy, d'Ascoli, Stéphane, Domingo-Enrich, Carles, Wu, Yuhuai, Li, Yuanzhi, Charton, François
We examine how transformers cope with two challenges: learning basic integer arithmetic, and generalizing to longer sequences than seen during training. We find that relative position embeddings enable length generalization for simple tasks, such as
Externí odkaz:
http://arxiv.org/abs/2306.15400